In the left menu, click

Plan

Capacity

. The Capacity Plan page opens. Click

What-If Analysis

and in the What-If Analysis page, click the

PLAN MIGRATION

button in the

Migration Planning: Public Cloud

card.

This feature of Capacity Optimization lets you to forecast successfully the impact of migrating a workload to a public cloud instance such as Amazon Web Services, IBM Cloud, Microsoft Azure, or Google Cloud. Slect the region where you want to migrate the workload. If the public clouds listed out of the box do not suit your needs, you can also define your own public cloud and upload a rate card.

In defining the profile of your workload, you have two options:

Configure the workload manually by specifying vCPUs, memory, storage, and expected use percentage.
Use an existing VM or VMs as templates, importing all the attributes of the selected VMs to your workload scenario. The system allows you to specify how many copies of each selected VM you want to add to the proposed workload.

When you have set the profile for the migrating workload, run the scenario to get the

VMware Aria Operations

analysis and assessment of your plan. You can also select up to three public clouds to compare results. Alternatively, you can save the scenario to edit or run later on. A list of saved scenarios is available in the

Saved Scenarios

tab on the What-If analysis page.

For a public cloud target, the system lets you know immediately if the workload proposed for migration fits or does not fit in the suggested location. For example, if you selected AWS and the workload fits, the results list the Amazon Web Services Assessment, with details of the VMware Configuration and the AWS Equivalent. If the proposed workload does not fit, an error message appears: "Unable to identify a matching configuration instance in target location."

The system might provide a recommendation based on the cost of placing the workload on different clouds. This cost-based recommendation varies for different clouds. You can modify the costs for public clouds by uploading a new rate card.

Public cloud costs are based on the selected configuration, that is, the allocated resources.

The public instance is selected based on the close proximity rule, with simulated resource allocation values. In some scenarios, an exact configuration match is not available in the list. Due to this lack of availability, the public cost can be inherently higher in comparison.